| 2023 | AsiaCCS | Extracting Privacy-Preserving Subgraphs in Federated Graph Learning using Information Bottleneck. | Chenhan Zhang, Weiqi Wang, James J. Q. Yu, Shui Yu |
| 2023 | ICDE | Uncertainty Quantification for Traffic Forecasting: A Unified Approach. | Weizhu Qian, Dalin Zhang, Yan Zhao, Kai Zheng, James J. Q. Yu |
| 2023 | VTC | FedVAE: Trajectory privacy preserving based on Federated Variational AutoEncoder. | Yuchen Jiang, Ying Wu, Shiyao Zhang, James J. Q. Yu |
| 2022 | WCNC | Graph-Based Traffic Forecasting via Communication-Efficient Federated Learning. | Chenhan Zhang, Shiyao Zhang, Shui Yu, James J. Q. Yu |
| 2021 | AAAI | Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning. | Christos Markos, James J. Q. Yu, Richard Yi Da Xu |
| 2021 | ICANN | TINet: Multi-dimensional Traffic Data Imputation via Transformer Network. | Xiaozhuang Song, Yongchao Ye, James J. Q. Yu |
| 2021 | ICANN | Spatial-Temporal Traffic Data Imputation via Graph Attention Convolutional Network. | Yongchao Ye, Shiyao Zhang, James J. Q. Yu |
| 2021 | IJCNN | A Bayesian Learning Network for Traffic Speed Forecasting with Uncertainty Quantification. | Ying Wu, James J. Q. Yu |
| 2021 | IJCNN | FedOVA: One-vs-All Training Method for Federated Learning with Non-IID Data. | Yuanshao Zhu, Christos Markos, Ruihui Zhao, Yefeng Zheng, James J. Q. Yu |
| 2021 | ICTAI | Attn-CommNet: Coordinated Traffic Lights Control On Large-Scale Network Level. | Jiashi Gao, Xinming Shi, James J. Q. Yu |
| 2021 | ICTAI | Improving Transportation Mode Identification with Limited GPS Trajectories. | Yuanshao Zhu, Christos Markos, James J. Q. Yu |
| 2020 | GLOBECOM | An Enhanced Motif Graph Clustering-Based Deep Learning Approach for Traffic Forecasting. | Chenhan Zhang, Shuyu Zhang, James J. Q. Yu, Shui Yu |
| 2020 | ICPADS | Robust Federated Learning Approach for Travel Mode Identification from Non-IID GPS Trajectories. | Yuanshao Zhu, Shuyu Zhang, Yi Liu, Dusit Niyato, James J. Q. Yu |